Advancements in Speech Recognition Set to Improve IVR

By Susan J. Campbell, TMCnet Contributing Editor

As much as we like automated systems, we also like to use voice to move through steps and complete interactions. Interactive Voice Response (IVR) plays an important part in this process and advancements in this technology over the past few years have removed customer frustration, replacing it with satisfied transaction completion.

This recent Plum Voice blog focused on the advancements in IVR, thanks to improvements in speech recognition. Customers no longer have to repeat themselves to be understood in advanced IVR environments. Increases in computer processing speeds have enabled speech recognition developers to create more natural, accurate speech recognition software.

IVR may soon get even better as it seems Microsoft (News - Alert) is set to give speech recognition another boost. The company’s research team has made what it considers to be a significant breakthrough in this technology. In essence, the Microsoft Research team has developed a way to leverage mathematical modeling of the brain with thousands of possible sounds in human speech known as senones.

Speech recognition software that would work better out-of-the-box for all users could be enabled through artificial and deep neural networks (ANNs and DNNs), which are mathematical models of the low-level circuits of the brain. Traditional speech recognition software required users to train the software to work well with their voice and dialect. This approach is inefficient for use in things like IVR for call center support, translation or other platforms where different people interact with the software.

This new approach to speech recognition and IVR could help designers by giving them the ability to use more parts of human speech. The larger parts of speech are the 30 or so phonemes used for pronunciation. Modern speech recognition software relies on senones, which are smaller and are in the thousands. Before the completion of the Microsoft study, researchers didn’t use senones with ANNs or DNNs.

The lesson learned? Essentially, speech recognition, and subsequently IVR, are set to take another significant step forward. Initial testing in this space found a 30 percent improvement in accuracy over modern speech recognition software. For those companies – and customers – relying on IVR to complete interactions, this improvement is significant. Susan J. Campbell is a contributing editor for TMCnet and has also written for eastbiz.com. To read more of Susan’s articles, please visit her columnist page.